Time Series and Spatial Characteristics of Public Attention towards Huangyan Island Based on Baidu Index

Abstract

Wang, J.; Lu, C.; Tang, J.; Ge, L.; Huang, Z., and Zhou, S., 2019. Time series and spatial characteristics of public attention towards Huangyan Island based on Baidu index. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 281-285. Coconut Creek (Florida), ISSN 0749-0208.Huangyan Island is the only exposed reef in central region of the South China Sea. It is of great strategic status in national economic development as well as homeland security. Based on Baidu's index data along with spatial autocorrelation analyse, this paper explores the spatial and temporal characteristics of public attention towards Huangyan Island. Deconstructing the changing process and spatial distribution of public sentiments towards Huangyan Island is conducive to government decision-making together with resolving disputes about the South China Sea. The results show that: (1) the search index is basically accord with the development trend of public attention. In line with the process of public opinion development, public sentiments towards Huangyan Island can be divided into three stages: stable stage, small conflict stage and outbreak stage. Overall, most of the time public sentiments are in moderate and stable stage. Occasionally some conflict will cause public attention fluctuate within a short time. If there is a larger conflict, it will lead to wide outbreak of public sentiments. (2) Most of Chinese people have awareness of Huangyan Island yet their degree of concern is distinct. Generally speaking, the spatial distribution of search index is higher in eastern coastal areas and lower in western inland areas. Nevertheless, in some western cities, the search index is also high. (3) The spatial autocorrelation results shows that the eastern coastal areas and Beijing area have the “high - high” correlation, and there is a “high - low” correlation in the provincial or key cities in central provinces.